Object Re-Identification Based on Deep Learning

With the explosive growth of video data and the rapid development of computer vision technology, more and more relevant technologies are applied in our real life, one of which is object re-identification (Re-ID) technology. Object Re-ID is currently concentrated in the field of person Re-ID and vehicle Re-ID, which is mainly used to realize the cross-vision tracking of person/vehicle and trajectory prediction. This chapter combines theory and practice to explain why the deep network can re-identify the object. To introduce the main technical route of object Re-ID, the examples of person/vehicle Re-ID are given, and the improvement points of existing object Re-ID research are described separately

Sustainability-based lifecycle management for bridge infrastructure using 6D BIM

A number of bridge infrastructures are rising significantly due to economic expansion and growing numbers of railway and road infrastructures. Owing to the complexity of bridge design, traditional design methods always create tedious and time-consuming construction processes. In recent years, Building Information Modelling (BIM) has been developed rapidly to provide a faster solution to generate and process the integration of information in a shared environment. This paper aims to highlight an innovative 6D BIM approach for the lifecycle asset management of a bridge infrastructure by using Donggou Bridge as a case study. This paper adopts 6D modelling, incorporating 3D model information with time schedule, cost estimation, and carbon footprint analysis across the lifecycle of the bridge project. The results of this paper reveal that raw materials contribute the most embodied carbon emissions, and as the 6D BIM model was developed in the early stage of the lifecycle, stakeholders can collaborate within the BIM environment to enhance a more sustainable and cost-effective outcome in advance. This study also demonstrates the possibility of BIM applications to bridge infrastructure projects throughout the whole lifecycle. The 6D BIM can save time by transforming 2D information to 3D information and reducing errors during the pre-construction and construction stages through better visualisation for staff training. Moreover, 6D BIM can promote efficient asset and project management since it can be applied for various purposes simultaneously, such as sustainability, lifecycle asset management and maintenance, condition monitoring and real-time structural simulations. In addition, BIM can promote cooperation among working parties and improve visualisation of the project for various stakeholders

Dynamical quantum phase transitions in a spinor Bose-Einstein condensate and criticality enhanced quantum sensing

Quantum phase transitions universally exist in the ground and excited states of quantum many-body systems, and they have a close relationship with the nonequilibrium dynamical phase transitions, which however are challenging to identify. In the system of spin-1 Bose-Einstein condensates, though dynamical phase transitions with correspondence to equilibrium phase transitions in the ground state and uppermost excited state have been probed, those taken place in intermediate excited states remain untouched in experiments thus far. Here we unravel that both the ground and excited-state quantum phase transitions in spinor condensates can be diagnosed with dynamical phase transitions. A connection between equilibrium phase transitions and nonequilibrium behaviors of the system is disclosed in terms of the quantum Fisher information. We also demonstrate that near the critical points parameter estimation beyond standard quantum limit can be implemented. This work not only advances the exploration of excited-state quantum phase transitions via a scheme that can immediately be applied to a broad class of few-mode quantum systems, but also provides new perspective on the relationship between quantum criticality and quantum enhanced sensing

HICF: Hyperbolic Informative Collaborative Filtering

Considering the prevalence of the power-law distribution in user-item networks, hyperbolic space has attracted considerable attention and achieved impressive performance in the recommender system recently. The advantage of hyperbolic recommendation lies in that its exponentially increasing capacity is well-suited to describe the power-law distributed user-item network whereas the Euclidean equivalent is deficient. Nonetheless, it remains unclear which kinds of items can be effectively recommended by the hyperbolic model and which cannot. To address the above concerns, we take the most basic recommendation technique, collaborative filtering, as a medium, to investigate the behaviors of hyperbolic and Euclidean recommendation models. The results reveal that (1) tail items get more emphasis in hyperbolic space than that in Euclidean space, but there is still ample room for improvement; (2) head items receive modest attention in hyperbolic space, which could be considerably improved; (3) and nonetheless, the hyperbolic models show more competitive performance than Euclidean models. Driven by the above observations, we design a novel learning method, named hyperbolic informative collaborative filtering (HICF), aiming to compensate for the recommendation effectiveness of the head item while at the same time improving the performance of the tail item. The main idea is to adapt the hyperbolic margin ranking learning, making its pull and push procedure geometric-aware, and providing informative guidance for the learning of both head and tail items. Extensive experiments back up the analytic findings and also show the effectiveness of the proposed method. The work is valuable for personalized recommendations since it reveals that the hyperbolic space facilitates modeling the tail item, which often represents user-customized preferences or new products.Comment: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22

Coupling mechanisms of displacement and imbibition in pore-fracture system of tight oil reservoir

Fracturing and water flooding have been popular technologies to achieve the effective development of tight oil reservoirs in recent years. However, in the late stage of production, the oil recovery rate declines with a rapid increase in the water cut. Water huff-puff could improve reservoir energy; however, the displacement and imbibition in the micro-nano pore throat and fracture systems are complex processes with unclear characteristics and position. Therefore, it is urgent to study the coupling mechanisms of oil-water displacement and imbibition in tight oil reservoirs. In this work, based on the phase field method of COMSOL Multiphysics software, we establish a two-dimensional microscopic numerical simulation model of the pore-fracture system, and carry out displacement-imbibition simulation programs of different injection media (water and surfactant) and injection methods (displacement, displacement-imbibition). By comparing the saturations and pressure distributions of different simulation programs, we analyze the changes in the oil-water interface, and summarize the action conditions of counter-current imbibition and pore throat limit. Finally, reasonable development suggestions are proposed for tight oil reservoirs.Cited as: Pi, Z., Peng, H., Jia, Z., Zhou, J, Cao, R. Coupling mechanisms of displacement and imbibition in pore-fracture system of tight oil reservoir. Capillarity, 2023, 7(1): 13-24. https://doi.org/10.46690/capi.2023.04.0